Categorical: Create a Categorical distribution In alexpghayes/distributions: Probability Distributions as S3 Objects

Description

Create a Categorical distribution

Usage

 `1` ```Categorical(outcomes, p = NULL) ```

Arguments

 `outcomes` A vector specifying the elements in the sample space. Can be numeric, factor, character, or logical. `p` A vector of success probabilities for each outcome. Each element of `p` can be any positive value – the vector gets normalized internally. Defaults to `NULL`, in which case the distribution is assumed to be uniform.

Value

A `Categorical` object.

See Also

Other discrete distributions: `Bernoulli()`, `Binomial()`, `Geometric()`, `HyperGeometric()`, `Multinomial()`, `NegativeBinomial()`, `Poisson()`

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```set.seed(27) X <- Categorical(1:3, p = c(0.4, 0.1, 0.5)) X Y <- Categorical(LETTERS[1:4]) Y random(X, 10) random(Y, 10) pdf(X, 1) log_pdf(X, 1) cdf(X, 1) quantile(X, 0.5) # cdfs are only defined for numeric sample spaces. this errors! cdf(Y, "a") # same for quantiles. this also errors! quantile(Y, 0.7) ```

alexpghayes/distributions documentation built on April 8, 2021, 5:55 a.m.